The Data Scientist role is responsible for modelling complex business problems, discovering insights and identifying opportunities using statistical, algorithmic, Machine Learning/Mining and visualization techniques. In addition to advanced analytic skills, this person needs to be proficient at integrating and preparing large, varied datasets and communicating results.
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The Manager will be a creative thinker and propose innovative ways to look at problems, the role works closely with clients, data stewards, project/program managers, and other IT teams to turn data into critical information and knowledge that can be used to make sound organizational decisions. The role is responsible for providing data that is congruent and reliable. These professionals will need a combination of business focus, strong analytical and problem-solving skills and strong programming knowledge to be able to quickly cycle hypothesis through the discovery phase of the project.
The role will validate findings using an experimental and iterative approach. The Data Scientist will need to present findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.
ExCo has mandated the establishment of a Business Intelligence Competency Centre to evolve BI practices to better serve MTN. The vision of the BICC is to create a permanent core BI organization in Group (BICC), staffed with highly skilled full-time professionals from across the enterprise. This unit will work with Tech BI and BICC teams in OpCos to leverage Group's BI capabilities and technology in support of the strategic initiatives of the business. In doing so, the BICC aims to achieve the following:
Enable each OpCo to provide BI competency suited to their needsAgility and efficiency in all BI-related activitiesSuitability and relevance of MTN-developed BI solutions, in Group and OpCosModels and frames business scenarios that are meaningful and which impact on critical business processes and/or decisionsThe ability to come up with solutions to defined business problems by leveraging pattern detection over potentially large datasets.Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters and geo-location information or social media, ability to work with structured/unstructured/semi structured data.Collaborates with subject matter experts to select the relevant sources of information & translates the business requirements into a data mining project.Adept at breaking down a project into its constituent phasesProficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.Utilizes patterns and variations in the volume, speed and other characteristics of data supporting the initiative, the type of data (e.g., images, text, clickstream or metering data) in predictive analysisMakes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.Educates the organization both from IT and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results. Helps the organization understand the principles and the math behind the process to drive organizational buy-inDefines the validity of the information, how long the information is meaningful, and what other information it is related to.Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.Experience with common data science toolkits, such as SAS, R, SPSS, etc Excellence in at least one of these is highly desirableExperience with data visualization tools, such as Power BI, Tableau, etc.Proficiency in using query languages such as SQL, Hive, Pig Experience with NoSQL databases, such as MongoDB, Cassandra, HBaseProficient communication skills & the ability to take complex outputs and present back to business owners4 years Bachelor's degree in mathematics, statistics or computer science or related fieldPost-graduate degree in a related analytic/engineering field is a plusExperience:
Minimum of 2 years of relevant work experience as a Data Scientist or Data Analyst, with experience building complex analytical models leveraging structured and/or unstructured dataDeep knowledge and experience in data analytics tools (SQL, Python, SAS, etc.)Deep knowledge and experience in data reporting/visualisation tools (Power BI, Tableau, etc
Competencies:Telecommunications IndustryInfluencing othersInformation processingProblem solvingAnalyticalData interpretationJudgmentReportingManaging technology and commercial personnelThe data scientist must be highly skilled in the design, development, and validation of descriptive, predictive, prescriptive, and applied Analytics
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